ArticleNature communications2024
ChromaFold predicts the 3D contact map from single-cell chromatin accessibility.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Foundation model reveals the shared organization of transcription and topologically associating domains.Cell systems · 2026Article
- Origins and consequences of oncogenic 3D chromatin remodelling.Nature reviews. Cancer · 2026Review
- Article
- Deep learning enabled prediction of nuclear lamina-associated chromatin.Patterns (New York, N.Y.) · 2026Article
- 3D genome architecture and epigenetic regulation of lineage identity in advanced prostate cancer.Endocrinology · 2026Review
- Metadomain and metaloop genome interactions in mammalian T cells.Cell reports · 2026Article
- UniversalEPI: robust prediction of cell type-specific and differential chromatin interactions from DNA sequence and chromatin accessibility.Nucleic acids research · 2026Article
- Large-scale data-driven pre-trained DNA models enhance performance across diverse genomics tasks.Nature communications · 2026Article
- Machine learning for evolutionary genetics and molecular evolution.Trends in genetics : TIG · 2026Review
- Hi-Compass: a depth-aware deep learning framework for predicting cell-type-specific 3D genome organization from single-cell to spatial resolution.Nature communications · 2026Article
- Mapping disease loci to biological processes via joint pleiotropic and epigenomic partitioning.Cell genomics · 2026Article
- Early feature extraction drives model performance in high-resolution chromatin accessibility prediction.Genome research · 2026Article
- Recent advances in single-cell bioinformatics for inferring higher-order chromatin contact maps.BMB reports · 2025Review
- Techniques to detect physical interactions between genomic regions.Epigenomics · 2025Review
- Genome structure mapping with high-resolution 3D genomics and deep learning.bioRxiv : the preprint server for biology · 2025Article
- Three-dimensional regulatory hubs support oncogenic programs in glioblastoma.Molecular cell · 2025Article
- Recipes and ingredients for deep learning models of 3D genome folding.Current opinion in genetics & development · 2025Review
- Integrating Single-Molecule Sequencing and Deep Learning to Predict Haplotype-Specific 3D Chromatin Organization in a Mendelian Condition.bioRxiv : the preprint server for biology · 2025Article
- TGF-β-driven T-cell exclusion in ovarian cancer: single-cell and spatial transcriptomic views of immune low-response states.Frontiers in immunology · 2025Review
- A review of deep learning models for the prediction of chromatin interactions with DNA and epigenomic profiles.Briefings in bioinformatics · 2024Review
Corrections and comments
- Erratum issued
- Update of
Authors and funding
24 authors.
Funding
Abstract
Identifying cell-type-specific 3D chromatin interactions between regulatory elements can help decipher gene regulation and interpret disease-associated non-coding variants. However, achieving this resolution with current 3D genomics technologies is often infeasible given limited input cell numbers. We therefore present ChromaFold, a deep learning model that predicts 3D contact maps, including regulatory interactions, from single-cell ATAC sequencing (scATAC-seq) data alone. ChromaFold uses pseudobulk chromatin accessibility, co-accessibility across metacells, and a CTCF motif track as inputs and employs a lightweight architecture to train on standard GPUs. Trained on paired scATAC-seq and Hi-C data in human samples, ChromaFold accurately predicts the 3D contact map and peak-level interactions across diverse human and mouse test cell types. Compared to leading contact map prediction models that use ATAC-seq and CTCF ChIP-seq, ChromaFold achieves state-of-the-art performance using only scATAC-seq. Finally, fine-tuning ChromaFold on paired scATAC-seq and Hi-C in a complex tissue enables deconvolution of chromatin interactions across cell subpopulations.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.